Identifying information assets within an enterprise using a semantic graph created using feedback re-enforced search and navigation

Abstract

Embodiments of the invention provide an approach for creating, evolving and using a weighted semantic graph to manage and potentially identify certain information assets within an enterprise. The semantic graph may be generated by monitoring users navigating through search results which provide a set of information assets responsive to a search query. By recording the navigation path taken by many users, relationships between information assets may be identified. Further, once generated, the semantic graph may be used to present users with an indication of related information assets as part of the search results. Further still, the semantic graph may also be used to identify information assets “hubs” as well as information assets that may provide low utility to individuals within the enterprise.

Description

BACKGROUND[0001]Embodiments of the invention are directed to techniques for managing information assets in an enterprise environments. More specifically, embodiments of the invention provide an information asset management tool configured to capture and utilize crowd wisdom in order to identify and share relationships about information assets within the enterprise.[0002]Organizations commonly have to manage very large-scale information systems, which can include a very large number of both interrelated and independent information assets. While information assets can vary in nature, examples include structured systems such as traditional relational databases as well as unstructured systems such as content repositories and document stores. The degree of formality with which these systems are monitored, registered and managed can vary extensively within a large enterprise. An enterprise typically manages mission-critical information systems. However, such systems are frequently outnumb...

AI Technical Summary

Benefits of technology

The patent describes a method for identifying information assets in an enterprise information management system. It involves monitoring user behavior to create a semantic graph of the underlying data. The graph is made up of nodes and edges, which represent the relationships between information assets. The method uses predefined criteria to evaluate the metadata of each node and creates an indication of the first node that satisfies the criteria. Overall, this method enables easier identification and management of information assets in enterprise settings.

Problems solved by technology

However, such systems are frequently outnumbered by unmanaged systems (e.g., spreadsheets, local database and document stores, as well as other information assets).

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